{
 "metadata": {
  "name": "Ra_effect_on_EPSCs"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<H1>Effect of the intracellular resistivity on EPSC</H1>\n",
      "\n",
      "This notebook will test the effect of different intracellular resisitivity on the\n",
      "EPSC waveform in a CA3 model of identical morphology. We have two cell types\n",
      "<ul>\n",
      "    <li>jonas: 294 $\\Omega \\cdot cm$, as in Jonas et al., 1993</li>\n",
      "    <li>christoph: 194 $\\Omega \\cdot cm$ as in Schmidt-Hieber et al., 2007</li> \n",
      "</ul>\n",
      "\n",
      "    "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "from neuron import h\n",
      "from CA3.library import christoph2007, jonas1993\n",
      "matplotlib.rcParams.update({'font.size': 20})"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<H3>Jonas CA3 cell</H3>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "jonas = jonas1993() # remember this is a function in /src/library\n",
      "jonas.morphinfo() # morphinfo is a method of the ca3_15 cell class\n",
      "print(jonas1993.__doc__)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "CA3b morphology with\n",
        "168 segments and 1628 sections\n",
        "basal dendrite ds[0] connected to right (1) soma\n",
        "basal dendrite ds[13] connected to right (1) soma\n",
        "basal dendrite ds[32] connected to right (1) soma\n",
        "basal dendrite ds[47] connected to right (1) soma\n",
        "apical dendrite ds[74] connected to left (0) soma\n",
        "apical dendrite ds[106] connected to left (0) soma\n",
        "apical dendrite ds[119] connected to left (0) soma\n",
        "\n",
        "\n",
        "    Creates a cell object with the following \n",
        "    passive properties homogenously distributed\n",
        "    Cm = 0.683  microF/cm^2\n",
        "    Rm = 164000 Ohms*cm^2 \n",
        "    Ra = 294    Ohms*cm  \n",
        "    just as described in Jonas et al., 1993\n",
        "    \n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "# for comparison, we set the specific membrane capacitance to 1\u00b5F/cm^2\n",
      "for sec in jonas.allsec:\n",
      "    sec.cm = 1 # in \u00b5F/cm^2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<H3>Christoph cell</H3>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "christoph = christoph2007()\n",
      "print(christoph2007.__doc__)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "    Creates a cell object with the following \n",
        "    passive properties homogenously distributed\n",
        "    Cm = 1  microF/cm**2\n",
        "    Rm = 164000 Ohms*cm**2 \n",
        "    Ra = 194    Ohms*cm  (Schmidt-Hieber 2007)\n",
        "    \n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<H3>Voltage-clamp at the soma</H3>\n",
      "<ul>\n",
      "    <li> holding potential -70 mV </li>\n",
      "    <li> series resistance 0.1 M$\\Omega$ </li>\n",
      "</ul>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "VC_patch1 = h.SEClamp(0.5, sec=jonas.soma)\n",
      "VC_patch1.rs = 0.1 # ms\n",
      "VC_patch1.amp1 = -70 # mV\n",
      "\n",
      "VC_patch2 = h.SEClamp(0.5, sec=christoph.soma)\n",
      "VC_patch2.rs = 0.1\n",
      "VC_patch2.amp1 = -70"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<H3>Fast AMPAR-like conductance at the soma</H3>\n",
      "needs synapse.mod compiled\n",
      "<ul>\n",
      "    <li> peak conductance  300 pS</li>\n",
      "    <li> tau on  0.2 ms </li>\n",
      "    <li> tau off  2.5 ms </li>\n",
      "</ul>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "mysyn1 = h.synapse(0.5, sec=jonas.soma) # described in synapse.mod\n",
      "mysyn1.tonset = 0 # ms\n",
      "mysyn1.tau0 = 0.2 # ms\n",
      "mysyn1.tau1 = 2.5 # ms\n",
      "mysyn1.gmax = 300e-6 # in microS"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "# create a new objet, do not use mysyn2 = mysyn\n",
      "mysyn2 = h.synapse(0.5, sec=christoph.soma) \n",
      "mysyn2.tonset = 0\n",
      "mysyn2.tau0 = 0.2\n",
      "mysyn2.tau1 = 2.5\n",
      "mysyn2.gmax = 300e-6 # in microS"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "# prepare simulation\n",
      "h.load_file('stdrun.hoc')\n",
      "\n",
      "def VC_simulation(tstop, synapse, pipette, with_time=False):\n",
      "    \"\"\"\n",
      "    runs the NEURON simulation and returns \n",
      "    current and time as NumPy arrays\n",
      "    Arguments:\n",
      "    tstop     -- duration of simulation\n",
      "    synapse   -- synapse to be stimulated\n",
      "    pipette   -- pipette from where we record\n",
      "    with_time -- if true, return time vector (in ms)\n",
      "\n",
      "\n",
      "    \"\"\"\n",
      "    \n",
      "    # setup simulation\n",
      "    h.v_init = -70\n",
      "    h.tstop = tstop\n",
      "    \n",
      "    # setup pipette\n",
      "    pipette.dur1 = tstop\n",
      "    \n",
      "    #  define hoc vectors\n",
      "    current = h.Vector()\n",
      "    current.record(pipette._ref_i)\n",
      "    if with_time is True:\n",
      "        time = h.Vector()\n",
      "        time.record(h._ref_t)\n",
      "    \n",
      "    h.run()\n",
      "    \n",
      "    mycurrent = np.array(current)*1000. # in pA\n",
      "\n",
      "    \n",
      "    if with_time is True:\n",
      "        time = np.array(time)\n",
      "        return(time, mycurrent) \n",
      "    else:\n",
      "        return(mycurrent)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "time, jonas_soma = VC_simulation(tstop = 25, synapse=mysyn1,  pipette=VC_patch1, with_time=True)\n",
      "christoph_soma = VC_simulation(tstop = 25, synapse=mysyn2, pipette=VC_patch2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# the effect is neligible if synapse is at the soma\n",
      "np.min(jonas_soma), np.min( christoph_soma)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "(-20.753939391653375, -20.688288439032476)"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(time, jonas_soma, 'r');\n",
      "plt.plot(time, christoph_soma);\n",
      "plt.xlabel('Time(ms)');\n",
      "plt.ylabel('Current (pA)');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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XWUM9PDyIiIggIsK9bxUdPXqUkSNHsmPHDgDatWtHdnY2hw8fvuV+s2bNAuCx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\n"
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "# provide a dramatic example (axial resistance 25 Ohms*cm)\n",
      "for sec in christoph.allsec:\n",
      "    sec.Ra = 25 # Ohms*cm"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "christoph_soma = VC_simulation(tstop = 25, synapse=mysyn2, pipette=VC_patch2)\n",
      "np.min(christoph_soma), np.min(jonas_soma)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "(-20.210824931155003, -20.753939391653375)"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<p>The effect of the axial resistance is neligible at the same compartment</p>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(time, jonas_soma, 'r');\n",
      "plt.plot(time, christoph_soma);\n",
      "plt.xlabel('Time(ms)');\n",
      "plt.ylabel('Current (pA)');\n",
      "plt.xlim(xmax=2);\n",
      "plt.legend(['294 $\\Omega$ cm', '25 $\\Omega$ cm']);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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xFyd6TVoBAQH4+flx+vRpHjx4QGxsLBUrVqRatWq0bduW3r1767eIbEnUoAHl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\njDFmMv4fcizH1DvUitAAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<H3>Distal dendritic location</H3>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# give again the axial resistance of 194 Ohms*cm)\n",
      "for sec in christoph.allsec:\n",
      "    sec.Ra = 194 # Ohms*cm\n",
      "\n",
      "# move synapes to basal dendrite\n",
      "mysyn1.loc(0.5, sec=jonas.ds[8])\n",
      "mysyn2.loc(0.5, sec=christoph.ds[8])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "0.5"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.distance(0, 0.5, sec = jonas.soma) #set soma to distance zero\n",
      "h.distance(0.5, sec = jonas.ds[8]) # get the distance to soma (in um)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "120.01885"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "time, jonas_dend = VC_simulation(tstop = 25, synapse=mysyn2, pipette=VC_patch1, with_time=True)\n",
      "christoph_dend = VC_simulation(tstop = 25, synapse=mysyn2, pipette=VC_patch2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(time, jonas_dend, 'r');\n",
      "plt.plot(time, christoph_dend);p\n",
      "plt.xlabel('Time(ms)');\n",
      "plt.ylabel('Current (pA)');\n",
      "plt.legend(['294 $\\Omega$ cm','194 $\\Omega$ cm']);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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GDRuKBQsWFEbxxc6TH/K4cYbvuzt4CTF1qoVrKKWnCxEYaPhcWrcWIilRK8SU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\n7u7o168fjh8/jr1790IqlaJVK7rkWRzT5khCTEuXnpSysvKelPwVERH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      }
     ],
     "prompt_number": 18
    }
   ],
   "metadata": {}
  }
 ]
}